{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T11:30:41Z","timestamp":1778758241654,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T00:00:00Z","timestamp":1629158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,17]]},"DOI":"10.1145\/3465481.3469190","type":"proceedings-article","created":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T17:57:21Z","timestamp":1629136641000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":98,"title":["A Hybrid CNN-LSTM Based Approach for Anomaly Detection Systems in SDNs"],"prefix":"10.1145","author":[{"given":"Mahmoud","family":"Abdallah","sequence":"first","affiliation":[{"name":"UCD, Ireland"}]},{"given":"Nhien","family":"An Le Khac","sequence":"additional","affiliation":[{"name":"UCD, Ireland"}]},{"given":"Hamed","family":"Jahromi","sequence":"additional","affiliation":[{"name":"UCD, Ireland"}]},{"given":"Anca","family":"Delia Jurcut","sequence":"additional","affiliation":[{"name":"UCD, Ireland"}]}],"member":"320","published-online":{"date-parts":[[2021,8,17]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8030322"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-017-2414-5"},{"key":"e_1_3_2_2_3_1","volume-title":"2019 International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), Vol.\u00a01. IEEE, 1\u20136.","author":"Sarra","year":"2019","unstructured":"Sarra BOUKRIA and Mohamed GUERROUMI. 2019. Intrusion detection system for SDN network using deep learning approach. In 2019 International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), Vol.\u00a01. IEEE, 1\u20136."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-01408-x"},{"key":"e_1_3_2_2_5_1","volume-title":"MOBILE AND MULTIMEDIA NETWORKS (IEEE WOWMOM","author":"Elsayed Mahmoud\u00a0Said","year":"2020","unstructured":"Mahmoud\u00a0Said Elsayed, Nhien-An Le-Khac, Soumyabrata Dev, and Anca\u00a0Delia Jurcut. [n. d.]. Ddosnet: A deep-learning model for detecting network attacks. In 21ST IEEE INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (IEEE WOWMOM 2020), Ireland. IEEE."},{"key":"e_1_3_2_2_6_1","volume-title":"Machine-Learning Techniques for Detecting Attacks in SDN. In 2019 IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 277\u2013281","author":"Elsayed Mahmoud\u00a0Said","year":"2019","unstructured":"Mahmoud\u00a0Said Elsayed, Nhien-An Le-Khac, Soumyabrata Dev, and Anca\u00a0Delia Jurcut. 2019. Machine-Learning Techniques for Detecting Attacks in SDN. In 2019 IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 277\u2013281."},{"key":"e_1_3_2_2_7_1","volume-title":"Detecting Abnormal Traffic in Large-Scale Networks. In 2020 IEEE International Symposium on Networks, Computers and Communications (ISNCC\u201920)","author":"Elsayed Mahmoud\u00a0Said","year":"2020","unstructured":"Mahmoud\u00a0Said Elsayed, Nhien-An Le-Khac, Soumyabrata Dev, and Anca\u00a0Delia Jurcut. 2020. Detecting Abnormal Traffic in Large-Scale Networks. In 2020 IEEE International Symposium on Networks, Computers and Communications (ISNCC\u201920). IEEE."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3022633"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSEC.2020.3037448"},{"key":"e_1_3_2_2_10_1","volume-title":"Anomaly Detection in Videos for Video Surveillance Applications Using Neural Networks. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC). IEEE, 632\u2013637","author":"Franklin J","year":"2020","unstructured":"Ruben\u00a0J Franklin, Vidyashree Dabbagol, 2020. Anomaly Detection in Videos for Video Surveillance Applications Using Neural Networks. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC). IEEE, 632\u2013637."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICOEI.2019.8862784"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics9101684"},{"key":"e_1_3_2_2_13_1","volume-title":"Long short-term memory. Neural computation 9, 8","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation 9, 8 (1997), 1735\u20131780."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2816564"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2973023"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1600970"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.12.019"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.3390\/app9194156"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Rocco Langone Alfredo Cuzzocrea and Nikolaos Skantzos. 2020. Interpretable Anomaly Prediction: Predicting anomalous behavior in industry 4.0 settings via regularized logistic regression tools. Data & Knowledge Engineering(2020) 101850.","DOI":"10.1016\/j.datak.2020.101850"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"Markus Ring Sarah Wunderlich Deniz Scheuring Dieter Landes and Andreas Hotho. 2019. A survey of network-based intrusion detection data sets. Computers & Security(2019).","DOI":"10.1016\/j.cose.2019.06.005"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3416013.3426457"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICREST.2019.8644161"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/WINCOM.2016.7777224"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/NETSOFT.2018.8460090"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/AINA.2016.158"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.08.047"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2018.2872054"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2904620"}],"event":{"name":"ARES 2021: The 16th International Conference on Availability, Reliability and Security","location":"Vienna Austria","acronym":"ARES 2021"},"container-title":["Proceedings of the 16th International Conference on Availability, Reliability and Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3465481.3469190","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3465481.3469190","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:17:29Z","timestamp":1750191449000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3465481.3469190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,17]]},"references-count":28,"alternative-id":["10.1145\/3465481.3469190","10.1145\/3465481"],"URL":"https:\/\/doi.org\/10.1145\/3465481.3469190","relation":{},"subject":[],"published":{"date-parts":[[2021,8,17]]},"assertion":[{"value":"2021-08-17","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}